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Due to environmental pollution, energy consumption, climate change and other reasons, the Chinese government proposed the “double carbon” goal to encourage the wide application of green technology. The green technology represented by CiteSpace has brought new ideas to the traditional study of American literature, which is conducive to energy conservation and emission reduction and the sustainable progress of scientific research. With the help of CiteSpace tool, this paper traces the hot spots and frontiers in the field of American literature research. Through the visualization research of knowledge map of green technology, we get valuable conclusions: first, the domestic research of American literature has gradually evolved from scattered stage to mature stage. Famous scholars such as Yukuo Wang, Ruoxi Pu, Li Jin, Jincai Yang and Ying Liu have emerged. And they have made landmark achievements in feminist criticism, historical context, new slave narrative, racial discrimination, spatial turn and so on. Second, the research object is diverse and rich, and the mainstream and tributaries blend. It includes ethnic groups such as Chinese and African Americans. It focuses on writers such as Maxine Hong Kingston, Faulkner, Melville, Whitman and Hemingway, including “intertextuality”, “tea culture”, “ecocriticism” and “Orientalism”. Third, although the current research on American literature is fruitful, the discrete and multivariate distribution of specific topics is significant. The use of green technology has brought new impetus to the study of traditional literature, greatly improved the efficiency of scientific research and reduced resource consumption. [ABSTRACT FROM AUTHOR]

Due to the increasingly serious problems of environmental pollution and resource waste, promoting the green and low-carbon transformation of education has become a new trend. Online foreign language education is a new mode of green transformation development relying on digital technology. Based on the new background of green technology, this paper focuses on the evaluation of online foreign language teaching satisfaction and the key influencing factors. The entropy weight method was used to construct the evaluation index of online foreign language teaching satisfaction, the multiple linear regression model and confirmatory factor analysis model were used to systematically analyze the main factors affecting the satisfaction, and the questionnaire was used to investigate the data of online foreign language courses such as American Literature, American Culture, College English, Comprehensive English, and History of Foreign Literature. The results show that: (1) college students have a high degree of satisfaction with online foreign language teaching, and the satisfaction index based on entropy weight method is above level 2. (2) Through the multiple linear regression model, the four dimensions of teaching involvement, teaching communication, teaching skills and teaching effect all have a significant impact on the satisfaction of online foreign language teaching. (3) Based on the confirmatory factor model, online foreign language teaching satisfaction is affected by multiple latent and explicit variables, and the effect direction is generally positive. Finally, the paper puts forward specific strategies to improve the effect of green and low-carbon digital technology on foreign language education. [ABSTRACT FROM AUTHOR]